mnist-cnn-tensorflow

"Convolutional Neural Network (CNN) for Handwritten Digit Recognition using TensorFlow and Keras. This code loads the MNIST dataset, preprocesses the images, builds a CNN model, and evaluates its performance. It also includes an example of making predictions on a custom test image."

Handwritten Digit Recognition with CNN

This repository contains Python code for a Convolutional Neural Network (CNN) designed to recognize handwritten digits. It uses the MNIST dataset for training and evaluation.

Contents

• digit_recognition_cnn.py: Python script containing the code.
• test_image.png: Example custom test image for prediction.

Getting Started

1. Clone the repository.
2. Run digit_recognition_cnn.py to train the model and make predictions.

Prerequisites

• Python 3.x
• TensorFlow
• Keras
• Matplotlib
• PIL

Install the necessary packages using pip install -r requirements.txt.

Usage

• Run digit_recognition_cnn.py to see the CNN in action.
• To make predictions on your own images, replace test_image.png with your custom image.

Results

• The model achieves an accuracy of XX% on the test set.

Acknowledgments

• The code in this repository is based on a tutorial by [Link to Tutorial].

Author

• Ganesh Adimalupu